
A United States federal judge has temporarily halted President Donald Trump’s directive to carry out large-scale layoffs of government workers, ruling that such action may require the approval of Congress.
Judge Susan Illston of the U.S. District Court in California issued a two-week restraining order on Friday, stating that the president likely overstepped his authority by ordering workforce cuts without involving lawmakers.

“The Court holds the President likely must request Congressional cooperation to order the changes he seeks,” Illston wrote, adding that the court was pausing the planned mass dismissals to prevent potential overreach.
The temporary order comes after a coalition of labour unions, non-profits, and six local governments sued the Trump administration, accusing it of bypassing congressional authority. The lawsuit targeted Trump, the newly formed Department of Government Efficiency (DOGE) led by tech billionaire Elon Musk, and several key agencies including the Office of Management and Budget.
President Trump, who returned to office in January, signed an executive order on February 11 calling for a sweeping overhaul of the federal bureaucracy. The order instructed agencies to eliminate non-essential roles as part of his administration’s broader plan to downsize government operations.
The American Federation of Government Employees (AFGE), which led the lawsuit, applauded the judge’s decision. “The Trump administration’s unlawful attempt to reorganise the federal government has thrown agencies into chaos,” the group said in a statement, warning that essential public services were being disrupted.
The administration has already begun efforts to cut thousands of federal jobs and shut down various programs, including those under the U.S. Agency for International Development (USAID), diversity offices, and others. However, legal challenges continue to stall some of the president’s major policy moves.
Trump’s drive to streamline government functions has sparked widespread debate, especially as critics argue it could lead to disorder rather than efficiency.
